发表机构
Shenzhen The Nine’s Light Technology Co., Ltd.（深圳九光科技有限公司）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究公共空间手势交互中从帧级识别到事件级确认的问题，通过分析工程修复记录提取故障实例并分类，构建事件级运行时抽象，贡献了基于部署的故障分类法、运行时抽象及案例研究结果。
AI 中文摘要
公共空间手势交互通常被评估为帧级识别问题，但部署系统呈现出不同的故障边界。在景区信息亭、展厅和服务终端中，用户体验的是预期动作是否成为稳定的交互事件，而非单个手部地标帧是否正确，我们称之为识别到交互的差距。本文分析了一个景区交互式信息亭项目的8份工程修复记录，涵盖4种手势任务。从这些痕迹中，提取了20个故障实例并将其组织成六个非排他性的工作故障类别。还将反复出现的修复机制组织成手部地标模型与交互任务之间的事件级运行时抽象。贡献包括基于部署的故障分类法、事件确认运行时抽象和案例研究结果。
英文摘要
Public-space gesture interaction is often evaluated as a frame-level recognition problem, but deployed systems expose a different failure boundary. In scenic kiosks, exhibition halls, and service terminals, users experience whether an intended action becomes a stable interaction event, not whether individual hand-landmark frames are correct. We call this the recognition-to-interaction gap. This paper analyzes 8 engineering repair records from a scenic-area interactive kiosk project, covering 4 gesture tasks: two-hand bowing, single-hand fist shaking, two-hand catching control, and knowledge-graph node hovering. From these traces, we extract 20 failure instances and organize them into six non-exclusive working failure classes: model-output degeneration, temporal mismatch, geometric-scale instability, coordinate-rendering mismatch, runtime lifecycle failure, and feedback synchronization and recovery failure. We further organize recurring repair mechanisms into an event-level runtime abstraction between the hand-landmark model and the interaction task. The contribution is deliberately bounded: a deployment-grounded failure taxonomy, an event-confirmation runtime abstraction, and case-study findings. We do not claim a new recognition model, large-scale user evaluation, or quantified accuracy gains.
Comments15 pages, 5 figures, 10 tables
